Analysis of Tropospheric Nitrogen Dioxide Using Satellite and Ground Based Data over Northern Thailand

Tropospheric NO2 columns over northern Thailand were analyzed using satellite products of the SCIMACHY, OMI, GOME-2A, and GOME-2B sensors for the 14-year period 2003–2016. The comparative results of the four pairs of different satellite datasets within overlapped years showed that they were well correlated with correlation coefficients (r) ranging from 0.82 to 0.88. The r-values improved to 0.85–0.90 when the analysis was considered only during the dry period (October to April). Ground in situ measurements of NO2 concentrations were also obtained for comparative analysis with the satellite NO2 columns. The results revealed relatively good agreement between these two parameters for a seasonal pattern. High levels of NO2 were detected by both satellite and ground monitoring during January–April with the maximum levels in March. Moreover, during this period, most satellite and ground datasets recorded greater levels of NO2 in the afternoon corresponding with the number of fire hotspots collected from the MODIS-Terra and -Aqua satellites. Satellite and ground measurements show slightly increasing annual trends of NO2 levels for 2010–2016 with values of 8.40 and 1.18 %, respectively, over the 6-year period

Comparison of variability and change rate in tropospheric NO2 column obtained from satellite products across China during 1997–2015

Tropospheric NO2 column (TNC) products retrieved from five satellites including GOME/ERS-2 (H, 1997–2002), SCIAMACHY (S, 2003–2011), OMI (O, 2005–2015), GOME-2/METOP_A (A, 2007–2013) and GOME-2/METOP_B (B, 2013–2015) were compared in terms of their spatiotemporal variability and changes over China. The temporal series of H suggested an increasing trend of TNC from 1997 to 2002, those of S, O and A revealed further increasing trends until the highest level of TNC was reached in 2011, but decreasing trends were detected by those of O and B from 2011 to 2015. Seasonally, TNC was the highest in winter and the lowest in summer. Variability and changes from satellite TNC products are also analyzed in different regions of China. Spatially, it was the highest in North China and the lowest in Tibetan Plateau based on five datasets. Overall, TNCs from A, B and S were higher than that from O; and TNC from S was larger than that from A at the country level. The higher TNC the region has, the larger difference satellite products would show. However, different datasets reached a good agreement in the spatial pattern of trends in TNC with highly significant increasing trends detected in North China